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Personal profile

Research interests

Beate’s research interests cover a wide variety of data analysis methods, from hypothesis testing, Bayesian statistics to machine learning, and optimal experimental design. Beate has experience working with pharmaceutical data, insurance data, and data in the social sciences.

Before joining the IMI, Beate worked as a Senior Research Statistician on pre-clinical data at AstraZeneca — a large pharmaceutical company. As part of Discovery Sciences, she designed and analysed experiments across the pre-clinical pipeline — from hit identification to animal experiments.

Her background is in mathematical statistics in which she completed a PhD at University College London (UCL) at the Department for Statistical Science. In her PhD, Beate worked on improving our understanding of community structure in large networks.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Statistical Sciences, Doctor of Philosophy, University College London

30 Sep 201230 Sep 2016

Award Date: 31 Dec 2016

Mathematics, Master of Science, Universität Bremen

30 Sep 200615 Jun 2012

Award Date: 15 Jun 2012

Keywords

  • Hypothesis testing
  • Bayesian statistics
  • Machine Learning
  • Networks
  • Optimal experimental design
  • Causality

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